updated PyPi version

build/lib/gradio/explain.py

@@ -1,59 +0,0 @@
-from gradio.inputs import Textbox
-from gradio.inputs import Image
-
-from skimage.color import rgb2gray
-from skimage.filters import sobel
-from skimage.segmentation import slic
-from skimage.util import img_as_float
-from skimage import io
-import numpy as np
-
-
-def tokenize_text(text):
-    leave_one_out_tokens = []
-    tokens = text.split()
-    leave_one_out_tokens.append(tokens)
-    for idx, _ in enumerate(tokens):
-        new_token_array = tokens.copy()
-        del new_token_array[idx]
-        leave_one_out_tokens.append(new_token_array)
-    return leave_one_out_tokens
-
-def tokenize_image(image):
-    img = img_as_float(image[::2, ::2])
-    segments_slic = slic(img, n_segments=20, compactness=10, sigma=1)
-    leave_one_out_tokens = []
-    for (i, segVal) in enumerate(np.unique(segments_slic)):
-        mask = np.copy(img)
-        mask[segments_slic == segVal] = 255
-        leave_one_out_tokens.append(mask)
-    return leave_one_out_tokens
-
-def score(outputs):
-    print(outputs)
-
-def simple_explanation(interface, input_interfaces,
-                       output_interfaces, input):
-    if isinstance(input_interfaces[0], Textbox):
-        leave_one_out_tokens = tokenize_text(input[0])
-        outputs = []
-        for input_text in leave_one_out_tokens:
-            input_text = " ".join(input_text)
-            print("Input Text: ", input_text)
-            output = interface.process(input_text)
-            outputs.extend(output)
-            print("Output: ", output)
-        score(outputs)
-
-    elif isinstance(input_interfaces[0], Image):
-        leave_one_out_tokens = tokenize_image(input[0])
-        outputs = []
-        for input_text in leave_one_out_tokens:
-            input_text = " ".join(input_text)
-            print("Input Text: ", input_text)
-            output = interface.process(input_text)
-            outputs.extend(output)
-            print("Output: ", output)
-        score(outputs)
-    else:
-        print("Not valid input type")

build/lib/gradio/interpretation.py

@@ -6,7 +6,6 @@ import numpy as np
 
 expected_types = {
     Image: "numpy",
-    Textbox: "str"
 }
 
 def default(separator=" ", n_segments=20):

gradio.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 1.0
 Name: gradio
-Version: 1.1.9
+Version: 1.2.0
 Summary: Python library for easily interacting with trained machine learning models
 Home-page: https://github.com/gradio-app/gradio-UI
 Author: Abubakar Abid

setup.py

@@ -5,7 +5,7 @@ except ImportError:
 
 setup(
     name='gradio',
-    version='1.1.9',
+    version='1.2.0',
     include_package_data=True,
     description='Python library for easily interacting with trained machine learning models',
     author='Abubakar Abid',